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WhiteStar Navigator

Giving, and Stories Through Maps

Selina Sandoval

Each year at WhiteStar, we give each employee $200 to donate to a cause they support.  WhiteStar values giving back something to the community, and this program has been well received by employees.   The only requirement is that the charity qualify for 5013(c) under the IRS tax code.  Other than that, the employee can choose any cause.  This year, we supported fifteen different causes from humane societies to cancer awareness to youth soccer and homeless organizations. Next year we hope to do even more.  

In other news, I wanted to publicly thank our partner Esri for an amazing game changing software product - Esri Story Maps. This web application lets you tell a story using your own maps, text, and data.  Think of how many times you have wanted to tell others about your project but cringed dragging visitors back to see a map on a monitor.  Using Esri Story Maps, you can tell your mapping story and then share it via a link in an email, blog, or newsletter. 

Here is a link to an interesting Esri Story Map on the bombing of Pearl Harbor marking the USA’s entrance into World War II.   Here is another Esri Story Map on some troublesome borders around the world.  Pointing  your browser to the Esri Story Maps site, you can see many additional examples.

At WhiteStar, we use Esri Story Maps to better communicate what we do.  If you are a GIS professional, you have doubtless felt frustrated explaining your job to people to others who do not work in the industry - “I’m in Maps.”  Using Esri Story Maps, we can now show people a snapshot of what we do along with explanatory text.  This entertaining example shows two Government Land Office (BLM) survey plat maps for a single township in Wyoming.  We georeferenced the old plat and the new plat.  Using the spyglass, you can move the lens over to compare the top map (oldest) with the underlying map (newest) to see the very dramatic differences.  Obviously keeping your digital land grid data up-to-date and not just downloading “whatever data you find” is critical.  In this case, it makes a difference of up to a mile in accuracy!

Here is another Esri Story Map example showing the entire lifeline of our data from ancient hardcopy map to digital vector data. 

Bottom line, our partnership with Esri - we’re a Silver Partner - brings value to our customers.  We understand, play with, and use a wide variety of Esri software offerings both in development and production, and then we share our expertise and quality products with you.   Without the partner program, we simply would not bring as much value in our offerings.

What’s in a Legal?

Selina Sandoval

White_Robert Company Photo.jpg

Land mapping lies at the core of natural resource businesses.  An organization must map its ownership and/or lease boundaries to thrive.  Historically this task has been done by hand, but new technology permits automations, accuracy,  and efficiencies.

Thirty US states use the Public Land Survey System (PLSS) devised by Thomas Jefferson as the basis for all land mapping. Land legals in the remaining states use bearings and distance (metes and bounds) to describe the boundary survey.  Texas, though a “metes and bounds” state, also uses PLSS-like legal descriptions in some areas, and references abstract-survey-block or lot-tract-subdivision in other areas.  Because of its unique history, Texas has many different surveying systems.

The Public Land Survey System (PLSS)

Land parcel legal descriptions within the PLSS reference the underlying land grid, i.e. meridian-section-township-range.  Legals may also reference permanent government lots or tracts within the section.  Legals containing references to lots, tracts, and quarter-quarters cannot be mapped without the detailed, granular, digitized data within each section.  Chaining the changes from these documents (or plats) together over the span of 200 years to produce the current “lay of the land” is critical to mapping legals accurately.

Metes and Bounds States

In metes-and-bounds states, there is sadly no intervening reference PLSS.  Survey boundaries exist as a chaotic set of  “shattered glass” polygons not necessarily tied to one another. In the northeastern states, it is more difficult to determine lease ownership as there is no index into a larger picture, permanent PLSS.  Interestingly, some organizations have tried to create a “pseudo PLSS” to reference polygons and wells in metes-and-bound states with varying degrees of success. The primary reason for failure is that such a pseudo-grid is not public domain and has no regulatory authority or tie to the land surveying community.  In different geographies, and in different companies one can see that mapping legals requires different resources, skills and tactics to create an accurate map.

The Challenges of Auto-Mapping

A real estate parcel or oil and gas lease can easily change geometry, owners, or other attributes frequently, whereas the PLSS seldom changes (we can, however, spend lots of effort capturing it increasingly more accurately).  A rural farm in Colorado may have the  PLSS legal description within the Sixth Principal Meridian, Township 8N 86W section 16  and a specific location within the section:  “LOTS 1,2,3,4, S/2 S/2 Tract 74”.  Naive software might “automagically” map the polygon within the north half of the north half of the section, but the original plats show these government lots and tracts to be firmly in the south half of the south half of the section, nearly ¾ of a mile away.

Would it not be nice to compute the legal boundary given the textual legal description instead of hand mapping it?  In the past, software programs have only been able to map legals using just the section polygon.  The  sectional subdivisions in the PLSS, i.e. lots, tracts, quarter quarters, and quarters of sections had not been digitized for most states, and poorly so in some government data.  This state of affairs has resulted in inaccurate, highly generalized maps.  Now that WhiteStar is building out that data for the 30 PLSS states, automated legal mapping is improving from 60-70% to well over 90%, the remainder are typically metes-and-bounds descriptions not referencing the PLSS.  You can save extraordinary amounts of money by mapping legals automatically using systems such as Quorum and high resolution data containing lots, tracts, and quarter-quarters captured from the original survey plats.

FOSS4G: Free Beer and the Longevity of Data

Selina Sandoval

White_Robert Company Photo.jpg

I just returned from a week in Bonn, Germany attending the annualInternational FOSS4G (Free and Open Source Software for Geospatial).  As always, this was a great venue for observing trends and improvements in the development of “free” software. The conference organizers are quick to point out that “free” does not mean zero cost as in a “free beer” but rather “free” in the sense of freely usable software and non-restrictive license agreements.

Healthy open source projects “grow” a community of frequently interacting developers, testers, and documenters. Individuals in the community assume roles and tasks to author frequent software releases.  Popular software developed in this manner includes everything from desktop GIS (QGIS, Grass) to databases (PostGIS on top of PostgreSQL) to various software level programing interfaces (Open Layers).  Many commercial products contain parts of FOSS4G products.

Unlike traditional commercial projects, open source projects are driven more broadly by projects requirements, funding, and community members.  There is no traditional “product roadmap” and features may spring up more haphazardly.  If there is a lot of interest in a particular functionality, it gets pushed to the front of the queue. 

FOSS4G offers workshops two days preceding the main event.  I took a workshop on the Internet of Things to learn how to collect and process real time sensor data.  The impending flood of sensor networks and data has huge implications for those of us in the natural resource industries in the United States and worldwide.  

In this workshop we connected a very low cost humidity/temperature sensor to an inexpensive Arduino interface.  We used software from the Swiss Earth Science Institute to interface the sensors, collect, and analyze the data in real time.  Using such technologies, a clever project to collect oil and gas well data could be similarly implemented.  

In contrast to prior years, there was more emphasis on GIS data.  Arnulf Cristl, a founder and charter member of OSGeo, gave an animated talk on “Software Comes and Goes. Mind the Data!”  You can watch the video here

Basically, Cristl makes the point that software needs to adapt and more fully utilize features in the data, and not the other way around.  In 100 years, data will likely be what has become permanent, and old software versions and companies long forgotten.  You should never adapt data to adjust to some vagary or fault in the software!